[Skip to main content](#main-content) [OpenNash Jobs](https://jobs.opennash.com/) [Hiring report](/reports/hiring/) · [All Lyft jobs](https://jobs.opennash.com/companies/lyft/) · [Search jobs](/search/) Lyft · New York, San Francisco, Seattle # Senior Data Scientist, Causal Inference New York, San Francisco, Seattle Senior individual contributor $136,160 - $170,240 Data & Analytics Listed on Lyft’s official careers site. Posted June 10, 2026. Check that it is still open and apply there. [Apply on Lyft’s careers site →](https://app.careerpuck.com/job-board/lyft/job/8584695002?gh_jid=8584695002) [OpenNash Jobs](https://jobs.opennash.com/) / [Lyft](https://jobs.opennash.com/companies/lyft/) / Senior Data Scientist, Causal Inference ## Job description At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Growth Products team drives rider and driver acquisition to scale the business and balance the marketplace. We specialize in incentive and messaging targeting, budget optimization, and paid media measurement, and move rapidly to test new ideas and products. As a Data Scientist expert in causal inference and marketing mix models (MMM), you will lead our efforts to measure and optimize investments across marketing channels. ### Responsibilities Deliver results across the entire lifecycle of data science solutions for Growth: from defining the problem with cross-functional stakeholders to deploying production models that address key business problems. Own complex domains and develop long-term roadmaps to maximize business impact. Build statistical pipelines, write production code, and design/analyze experiments. Participate in the science on-call rotation to ensure automated campaigns operate successfully. ### Experience Advanced degree in statistics, economics, mathematics, or equivalent industry experience. 4+ years of industry experience in causal inference or data science. Proven ability to apply statistics to unstructured problems and deliver measurable results. Deep technical expertise in causal inference and tackling challenging measurement problems. Expertise in marketing mix modeling is highly preferred. Expertise in SQL and experience with large-scale data platforms. Proficiency in Python and working within production coding environments. ### Benefits Great medical, dental, and vision insurance options with additional programs available when enrolled Mental health benefits Family building benefits Child care and pet benefits 401(k) plan with company match to help save for your future In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible Subsidized commuter benefits Monthly Lyft credits and complimentary Lyft Pink membership Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law. Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid The expected base pay range for this position in the Seattle area is $136,160 - $170,240, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process. ## At a glance - Posted by the employer: Jun 10, 2026 - First seen by OpenNash: Jul 10, 2026 - Last checked: Oct 18, 2026 - Listed for: 130 days - Location: New York, San Francisco, Seattle - Pay: $136,160 - $170,240[Apply on Lyft’s careers site →](https://app.careerpuck.com/job-board/lyft/job/8584695002?gh_jid=8584695002) ## More jobs at Lyft ### [Analytics Lead, Airports](https://jobs.opennash.com/companies/lyft/jobs/f9e55e49e6bf438d00ed/) Toronto ### [Analytics Lead, Central Market Management](https://jobs.opennash.com/companies/lyft/jobs/26f5b56c523ecd33ac87/) Toronto ### [Analytics Lead, Decisions & Insights](https://jobs.opennash.com/companies/lyft/jobs/872cadc4cfe6a0608e43/) New York ## Similar jobs at other companies ### [Senior Data Scientist, Experimentation & Causal Inference](https://jobs.opennash.com/companies/apple/jobs/cb20dff8e37bd31aee5b/) Apple · Cupertino, United States of America ### [Staff Machine Learning Scientist, Applied Causal Inference](https://jobs.opennash.com/companies/doordash/jobs/5c7f816c6fc58dda961c/) DoorDash · San Francisco, CA ### [Staff Machine Learning Engineer, Causal Inference](https://jobs.opennash.com/companies/doordash/jobs/25dc0a0bdcf0ba3e32a0/) DoorDash · San Francisco, CA ### [PhD Economics Intern – Reduced Form Causal Inference, Summer 2027](https://jobs.opennash.com/companies/amazon/jobs/510df53f99fb19c507b1/) Amazon · US, WA, Seattle [Data & Analytics jobs](/functions/data-analytics/) OpenNash lists jobs from employers’ own careers sites and does not handle applications. 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